optimize and predict antidepressant efficacy for patient with mdd using multi-omics analysis and ai-predictive tool

Conditions: Major Depressive Disorder

Summary: opade is a non-profit, observational, multicenter, open-label study aimed at defining personalized treatment for major depressive disorder (mdd). in particular, we will combine genetics, epigenetics, microbiome, immune response data together with anamnesis, questionnaires, electroencephalography (eeg) collected from subjects suffering mdd. eventually, an artificial intelligence (ai)/machine learning (ml) predictive tool will be created to guide clinicians in improving mdd treatment and patient's stratification.

three hundred and fifty patients diagnosed with mdd will be enrolled for 24 months and divided into 4 groups according to age: 14-17 years (70 pediatric patients), 18-30 years (100 adult patients), 31-39 years (90 adult patients), 40-50 years (90 adult patients). the study protocol includes 6 follow-up visits: t0 (enrollment), t1, t2, t3, t4, and t5. at each medical visit, psychometric questionnaires will be administered to the patients and contextual biological samples including blood, stool and saliva will be collected. the study will use a multi-omics approach including: metagenomic sequencing to characterize the microbiome composition; metabolomics to detect circulating metabolites; transcriptomics to quantify micrornas; epigenomics to assess methylation variability between and within groups and immune assays to analyze the antibody immune response and inflammatory profiles (cytokines, interleukins and growth factors). cortisol and lipoproteins will also be quantified. in parallel, cognitive assessment and emotional status will be recorded remotely by each patient via chatbot and wearable eeg devices, respectively. specifically, the chatbot will collect patient's conversations and monitoring her/his feelings; the chat conversation will be than transformed in a machine-readable data. the eeg device is a mobile app that will also allows to associate brainwaves with patients' feelings.

Eligibility criteria:
inclusion criteria: * patients diagnosed with major depressive disorder as certified by a scid 5 (structured clinical interview for dsm-5) for dsm-s for adults and k-sads-pl-dsm 5 (kiddie schedule for affective disorders and schizophrenia - present and lifetime for dsm 5) for adolescents. * currently experiencing a major depressive episode with a ham-d (hamilton depression) score of 18 or greater, or alternatively, a madrs (montgomery-asberg depression rating scale) score of 18 or greater. * about to start a new antidepressant. * not concurrently starting a new psychotropic medication. * age 14-50 years. * able to use mobile devices (smart phone, tablet). * willingness to provide written informed consent to participate. exclusion criteria: * intellectual disability. * neurological disease (multiple sclerosis, severe neurocognitive disorder, epilepsy). * current psychotic disorder or mood disorder with psychotic features. * primary diagnosis of alcohol or substance use disorder (dsm-5). * patients who started concomitant psychotropic medications less than one week ago. * active, ongoing inflammatory diseases (such as rheumatoid arthritis and rheumatic polymyalgia). or severe and unstable physical illness (such as recent myocardial infarction). * a history of hepatitis b or c, human immunodeficiency virus, or evidence of active tuberculosis infection or any active systemic infection within 2 weeks prior to the start of the study. * use of antibiotics or other medications that may have affected the composition of the microbiota during the 30 days prior to baseline. * pregnancy and lactation.

Keywords: major depressive disorders microbiome metabolomic transcriptomics inflammation immune response profiling genetics artificial intelligence machine learning electroencephalography chatbot biomarkers personalized medicine